Evaluation of the quality indicators of food-grade glycerin derived from different oil/fat raw materials

The relevance of the research is determined by the growing demand for food-grade glycerin and the need for an objective, comprehensive assessment of its quality. In modern domestic and global food technologies, glycerin-containing products are characterized by a wide range of functional properties: it is used as a sweetener in confectionery, an emulsifier to prevent the stratification of fat systems, a solvent for uniform distribution of biologically active components, as well as as a safe additive in the production of beverages, alcoholic beverages, pasta and dried fruits. The combination of these properties gives glycerin a significant place not only in the European but also in the global market for the food and processing industry. In this regard, the priority research area is the improvement of approaches to assessing product quality by comprehensively analyzing its properties. The purpose of this study is to determine the quality of glycerin-containing products obtained from oil and fat raw materials using the developed mathematical models of polygons for numerical analysis. The assessment was carried out using a set of indicators, including color, relative density, density at 20 °C, reaction to an alkaline medium, mass fractions of glycerin and ash, and the saponification coefficient. This enabled the formation of dimensionless complexes and the numerical analysis of the compliance of the studied samples with regulatory requirements. Experimental data processing and the calculation of quality criteria were performed using programming methods and the Excel environment, enabling us to develop geometric quality models and determine the required parameters for calculations. According to the studies, samples obtained from technical animal fats and rapeseed oil do not meet regulatory requirements, exceeding the average quality indicators by more than 3.5 times. Instead, the best characteristics were demonstrated by samples of sunflower and soybean oil, which correspond to the maximum regulatory values, while the average indicators exceeded the regulatory values by 14% to 24%. The proposed mathematical models can be effectively used to assess the condition of objects of varying complexity, provided that a wide range of physical, mechanical, chemical, and biological characteristics is considered, thereby ensuring the objectivity and scientific validity of the results.